Johann Brehmer

28 papers A* 6A 1Journal 21

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Differentiable and Learnable Wireless Simulation with Geometric Transformers. ICLR Thomas Hehn, Markus Peschl, Tribhuvanesh Orekondy, Arash Behboodi, Johann Brehmer
2025	J	`jnl`	Does equivariance matter at scale? Trans. Mach. Learn. Res. Johann Brehmer, Sönke Behrends, Pim de Haan, Taco Cohen
2024	J	`jnl`	A Lorentz-Equivariant Transformer for All of the LHC. CoRR Johann Brehmer, Victor Bresó, Pim de Haan, Tilman Plehn, Huilin Qu, Jonas Spinner, Jesse Thaler
2024	J	`jnl`	Deconfounding Imitation Learning with Variational Inference. Trans. Mach. Learn. Res. Risto Vuorio, Pim de Haan, Johann Brehmer, Hanno Ackermann, Daniel Dijkman, Taco Cohen
2024	J	`jnl`	Does equivariance matter at scale? CoRR Johann Brehmer, Sönke Behrends, Pim de Haan, Taco Cohen
2024	A	`conf`	Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers. AISTATS Pim de Haan, Taco Cohen, Johann Brehmer
2024	A*	`conf`	Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics. NeurIPS Jonas Spinner, Victor Bresó, Pim de Haan, Tilman Plehn, Jesse Thaler, Johann Brehmer
2024	J	`jnl`	Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics. CoRR Jonas Spinner, Victor Bresó, Pim de Haan, Tilman Plehn, Jesse Thaler, Johann Brehmer
2024	J	`jnl`	Probabilistic and Differentiable Wireless Simulation with Geometric Transformers. CoRR Thomas Hehn, Markus Peschl, Tribhuvanesh Orekondy, Arash Behboodi, Johann Brehmer
2023	A*	`conf`	EDGI: Equivariant Diffusion for Planning with Embodied Agents. NeurIPS Johann Brehmer, Joey Bose, Pim de Haan, Taco S. Cohen
2023	J	`jnl`	EDGI: Equivariant Diffusion for Planning with Embodied Agents. CoRR Johann Brehmer, Joey Bose, Pim de Haan, Taco Cohen
2023	J	`jnl`	Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers. CoRR Pim de Haan, Taco Cohen, Johann Brehmer
2023	J	`jnl`	FoMo Rewards: Can we cast foundation models as reward functions? CoRR Ekdeep Singh Lubana, Johann Brehmer, Pim de Haan, Taco Cohen
2023	A*	`conf`	Geometric Algebra Transformer. NeurIPS Johann Brehmer, Pim de Haan, Sönke Behrends, Taco S. Cohen
2023	J	`jnl`	Geometric Algebra Transformers. CoRR Johann Brehmer, Pim de Haan, Sönke Behrends, Taco Cohen
2023	J	`jnl`	Instance-Adaptive Video Compression: Improving Neural Codecs by Training on the Test Set. Trans. Mach. Learn. Res. Ties van Rozendaal, Johann Brehmer, Yunfan Zhang, Reza Pourreza, Auke J. Wiggers, Taco Cohen
2022	J	`jnl`	Deconfounded Imitation Learning. CoRR Risto Vuorio, Johann Brehmer, Hanno Ackermann, Daniel Dijkman, Taco Cohen, Pim de Haan
2022	A*	`conf`	Weakly supervised causal representation learning. NeurIPS Johann Brehmer, Pim de Haan, Phillip Lippe, Taco S. Cohen
2022	J	`jnl`	Weakly supervised causal representation learning. CoRR Johann Brehmer, Pim de Haan, Phillip Lippe, Taco Cohen
2021	J	`jnl`	Implicit Neural Video Compression. CoRR Yunfan Zhang, Ties van Rozendaal, Johann Brehmer, Markus Nagel, Taco Cohen
2021	J	`jnl`	Instance-Adaptive Video Compression: Improving Neural Codecs by Training on the Test Set. CoRR Ties van Rozendaal, Johann Brehmer, Yunfan Zhang, Reza Pourreza, Taco S. Cohen
2020	A*	`conf`	Flows for simultaneous manifold learning and density estimation. NeurIPS Johann Brehmer, Kyle Cranmer
2020	J	`jnl`	Flows for simultaneous manifold learning and density estimation. CoRR Johann Brehmer, Kyle Cranmer
2020	J	`jnl`	Hierarchical clustering in particle physics through reinforcement learning. CoRR Johann Brehmer, Sebastian Macaluso, Duccio Pappadopulo, Kyle Cranmer
2020	J	`jnl`	MadMiner: Machine Learning-Based Inference for Particle Physics. Comput. Softw. Big Sci. Johann Brehmer, Felix Kling, Irina Espejo, Kyle Cranmer
2019	J	`jnl`	The frontier of simulation-based inference. CoRR Kyle Cranmer, Johann Brehmer, Gilles Louppe
2018	J	`jnl`	Likelihood-free inference with an improved cross-entropy estimator. CoRR Markus Stoye, Johann Brehmer, Gilles Louppe, Juan Pavez, Kyle Cranmer
2018	J	`jnl`	Mining gold from implicit models to improve likelihood-free inference. CoRR Johann Brehmer, Gilles Louppe, Juan Pavez, Kyle Cranmer